A convenient rhetoric or substantial change of teacher racial diversity? A text mining analysis of federal, state, and district documents

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Abstract

Teacher racial diversity has been widely considered important in education. However, it remains unclear to what extent and how teacher racial diversity has been addressed at the federal, state, and district levels. In this study, we employed text mining to collect and analyze over three million documents at the federal, state, and district levels. We found that while students of color had disproportionately less access to racially diverse teachers, the documents under our analysis insufficiently discussed the recruitment and retention of racially diverse teachers. Our findings also reveal that education agencies at the federal, state, and district levels paid scant attention to recruiting and retaining Hispanic teachers. For the states and districts that discussed the recruitment of racially diverse teachers, they primarily recruited teachers from institutions and organizations that primarily serve people of color, such as Historically Black Colleges and Universities, the Columbia Latino/a Law Student Association, the National Association of Asian American Professionals, and the National Black MBA Association. Given the findings and the projected growth of Black and Hispanic student enrollment in the United States, we provide five policy recommendations for policymakers and leaders to racially diversify the teacher workforce amid shifting student demographics, particularly Hispanic students.

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How to Cite
Lee, S. H., Keith, B. N., Bey, Y., Wang, Y., Yang, X., Li, X., & Ji, S. (2022). A convenient rhetoric or substantial change of teacher racial diversity? A text mining analysis of federal, state, and district documents. Education Policy Analysis Archives, 30, (78). https://doi.org/10.14507/epaa.30.6677
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Author Biographies

Sing Hui Lee, Georgia State University

Sing Hui Lee received her PhD in political science at Georgia State University, with research interests focusing on youth political attitudes and behaviors in East Asia and Southeast Asia, youth activism, digital politics, and the role of identity in international relations studies. She received her LLM in international law from The University of Hull and LLM in international relations from Xiamen University. Lee is one of the board members of Daisy Alliance, a nongovernmental organization dedicated to enhancing global peace and strengthening nuclear nonproliferation and disarmament movement through grassroots and educational institution advocacy initiatives.

Briana N. Keith, Georgia State University

Briana N. Keith is a doctoral student in sociology at Georgia State University, with a concentration in life course and health. She has received her M.A. in gerontology at Georgia State University and her B.S. in anthropology and human biology at Emory University. Currently, she is working on research looking into the mental health effects of microaggressions of students and faculty of color in predominantly white institutions.

Yasmine Bey, Georgia State University

Yasmine Bey is a PhD student at Georgia State University in educational policy studies, with a concentration in research, measurement, & statistics. She works in the Center for Evaluation and Research Services at Georgia State University and has a background in social work and nonprofit management.

Yinying Wang, Georgia State University

Yinying Wang is an associate professor of educational leadership in the Department of Educational Policy Studies at College of Education and Human Development in Georgia State University. Her research interest intersects technology, decision making, emotions, and social network analysis in educational leadership and policy. In addition to teaching educational leadership courses, she also teaches social network analysis. Her background includes medical doctor, classroom teacher, and school administrator.

Xiulong Yang, Georgia State University

Xiulong Yang is a PhD student in the Department of Computer Science at Georgia State University. His research interests include deep neural network, data efficiency in deep learning, educational technology, and data mining.

Xiang Li, Georgia State University

Xiang received his bachelor’s degree in electrical engineering from Donghua University, China, in 2013, and his master’s degree in pattern recognition from Northeastern University, China, in 2018. He is currently pursuing a PhD degree in computer science at Georgia State University. His research interests include the robustness and interpretability of deep neural network, and brain MRI image analysis.

Shihao Ji, Georgia State University

Dr. Shihao Ji is an associate professor in the Computer Science Department at Georgia State University. His principal research interests lie in the area of machine learning and deep learning with an emphasis on high-performance computing. He is interested in developing efficient algorithms that can learn from a variety of data sources (e.g., image, audio, and text) on a large scale and automate decision-making processes in dynamic environments. Dr. Ji received his PhD in Electrical and Computer Engineering from Duke University in 2006. After that he was a research associate at Duke for about 1.5 years. Prior to joining GSU, he spent about 10 years in industry research labs. He is a senior member of the IEEE.